Great Recession & Slow Recovery

The Good, The Bad, and the Ugly

The Good:

• Student explored data on both FRED and World Bank Data

• Student picked relevant variables, explained it correctly

• Cogent international comparisons of the great recession

The Bad:

• Great interactive tools made for poor visualizations (at least default values)

• Time consuming to reproduce - Return to website, download image, etc.

The Ugly:

• Inconsistent style across FRED and World Bank Data

• Very difficult to see much of the text

Introduction

• Created an R package, ecodata, to facilitate visualizing data in undergraduate macroeconomics courses

• Wrapper for the fredr, wbstats, and ggplot2 packages

• Makes it easy to:

  • Download data from the Federal Reserve Economic Data (FRED) and World Bank databases

  • Produce professional-quality data visualizations

  • View descriptions of the data

  • Cite sources

• Do everything with 3-4 lines of code

• Not a substitute for fredr, wbstats, or ggplot2, nor for exploring data and using interactive tools in FRED and World Bank Data

Let’s Try It Out!

Fast Example: Two Lines of Code

mydata <- get_ecodata("https://fred.stlouisfed.org/series/MORTGAGE30US")
ggplot_ecodata_ts(mydata, title = "Mortgage Interest Rate - Fixed Rate 30-Year", plot.recessions = TRUE)

Student Example: Fetch the Data

# Identify what variables I want
# Includes both FRED and World Bank Data sources
variable_sources <- c(
  "https://fred.stlouisfed.org/series/UNRATE",
  "https://fred.stlouisfed.org/series/AURUKM",
  "https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG?locations=US",
  "https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG?locations=GB"
)

# Optionally, provide my own names for the variables
variable_names <- c(
  "Unemployment Rate: United States",
  "Unemployment Rate: United Kingdom",
  "Inflation Rate: United States",
  "Inflation Rate: United Kingdom"
)

# Fetch the data 
mydata <- get_ecodata(variable_sources, variable_names)

# Get only Great Recession + Recovery
mydata <- mydata |>
  filter(Date >= "2007-01-01" & Date <= "2016-12-31")

Student Example: Plot the Data

ggplot_ecodata_facet(mydata, 
                     ncol = 2, 
                     title = "Unemployment and Inflation in U.S. and U.K.",
                     plot.recession = TRUE)

Student Example: Data Description

ecodata_description_table(mydata)

Documentation

• All the documentation: https://murraylax.org/ecodata/

• Getting Started Guide

  • Walks through many of the most common uses of the package.

  • Download data for multiple states or countries with ease

  • Plots with multiple variables, bar plots

  • Data transformations, computing new quantities

• Full reference manual

• Instructional Vignettes

  • Short applications of the package to macroeconomic principles

Why Scripting Languages?

Why Avoid Scripting Languages?

ECODATA Package

• Gentle learning curve!

• Easy to do easy things

• Use simple reproducible code to analyze macroeconomics principles

Why ECODATA for Principles of Macroeconomics?

• Data visualization is a key skill for everyone

• Early introduction makes subsequent classes easier

• Data is used throughout the economics discipline, it should be used throughout economics curriculum

• Repeated practice throughout undergraduate degree builds mastery

Instructional Vignettes

• Supply and Demand for Housing

  • Data on construction prices, new house prices, and housing starts.

  • Does a supply and demand model prediction explain the data?

• Exchange Rates and Interest Rates

  • Data on exchange rates and interest rates interest rates in U.K. and U.S.

  • Does a supply and demand model for currencies explain the data?

• Unemployment and Recessions

  • State and national data on unemployment and during the 2008-2009 recession.

• And I will be making a lot more!

Best Practices for Principles-Level

• Show students worked-out examples - See my vignettes!

• Create prompts that require only 1-2 lines of code to answer the question

• Make economics real: Compare theoretical predictions with recent data

• Be mindful of opportunity costs - Do more data analysis means doing less of something else in the class

  • I plan on 3 or 4 short assignments for the semester

What Are Your Ideas?

• You have or envision a short low-stakes assignment where students visualize macroeconomic data?

• Answer these questions about one such assignment:

  1. What is the macroeconomics concept or theory that students apply?

  2. What variables do the students need?

  3. What will the students discover?

• Share your ideas! Email: jmurray@uwlax.edu

• What me to create instructional vignette around your idea? Let me know!

Thank you!